code: def forward(self, z_src, z_dst, edge_label_index):
      row, col = edge_label_index
      z = torch.cat([z_src[row], z_dst[col]], dim=-1)
  
      z = self.lin1(z).relu()
      z = self.lin2(z)
      return z.view(-1)
  
imports: import os.path
  import torch
  import torch.nn.functional
  import tqdm
  from sklearn.metrics import roc_auc_score
  from torch.nn import Embedding, Linear
  import torch_geometric.transforms
  from torch_geometric.datasets import Taobao
  from torch_geometric.loader import LinkNeighborLoader
  from torch_geometric.nn import SAGEConv
  from torch_geometric.utils.convert import to_scipy_sparse_matrix
label_desc: Use image node_id 2 for calling the EdgeDecoder obj's underlying member method code with example usage: obj.forward(z_src, z_dst, edge_label_index) and returns: z